1. Field
Embodiments of the present disclosure relate to an electric equipment that performs voice recognition and a control method thereof.
2. Description of the Related Art
In recent years, attempts to operate electronic products frequently used for daily life using a voice command have been made in various fields.
Particularly, a washer and a dishwasher reduce housework to provide living convenience and a television and an audio system occupy important positions in leisure, information collection, education, etc.
In addition, a remote controller is used to improve operational convenience. As a result, a user may perform desired operation using a hand while being seated.
However, such operation may cause operation of other equipments, which may restrict convenience. For this reason, an apparatus that is capable of recognizing a human voice is under development.
A voice recognition principle is as follows.
First, a voice recognition algorithm may mainly include a voice section detection process, a feature extraction process, and a matching process.
When a voice signal is input through a microphone, an analog/digital (A/D) converter converts the voice signal into a digital signal. The digital signal is output to a voice section detection unit.
The voice section detection unit divides the digital voice signal into short-section signals (i.e. frames), detects only a real voice section from the input signal using energy of each frame, a zero crossing rate, and time length information, and outputs the detected voice section to a feature extraction unit.
The feature extraction unit extracts a feature of a frame corresponding to the voice section to form a test pattern of the input voice and outputs the test pattern to a matching unit.
The matching unit compares the test pattern with reference patterns stored in a memory for reference data to output a reference pattern most similar to the test pattern to the recognized voice.
A reference pattern of a voice signal is stored in the memory for reference data as follows. The feature extraction unit extracts a feature of a frame corresponding to a voice section to form a reference pattern and stores the reference pattern in the memory for reference data. This process is repeatedly performed on voice signals to be recognized and obtained reference patterns are stored in the memory for reference data as a database.
In the conventional voice recognition method as described above, the voice section is extracted using information, such as short-section energy of a signal and a zero crossing rate.
These features indicate features of a signal in a time domain. Since complex calculation is not necessary, the features may be rapidly and conveniently used.
In a case in which voice recognition is applied to a washer, a performance in extracting a voice section using short-section energy of a signal or a zero crossing rate is lowered because surrounding noise and sound are great due to driving of a motor of the washer and water supply when a voice command to change a function is input during operation, e.g. washing, of the washer.
Consequently, a voice section extraction algorithm based on a new method using new features excluding energy and a zero crossing rate to stably extract a voice section regardless of surrounding noise and sound may be necessary.